Determinants of decline in resting metabolic rate in ... - Michael Goran

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STUART M. MONTGOMERY,. MICHAEL ... of Medicine and Department of Nutritional Sciences, University of Vermont, Burlington, Vermont 05405. Poehlman,.
Determinants of decline in resting metabolic rate in aging females ERIC T. POEHLMAN, MICHAEL I. GORAN, ANDREW W. GARDNER, PHILIP A. ADES, PAUL J. ARCIERO, SHANE M. KATZMAN-ROOKS, STUART M. MONTGOMERY, MICHAEL J. TOTH, AND PHUONG T. SUTHERLAND Divisions of Endocrinology, Metabolism and Nutrition, and Cardiology, Department of Medicine, of Medicine and Department of Nutritional Sciences, University of Vermont, Burlington, Vermont 05405

College

composition in middle-aged women. No studies, to our knowledge, have considered the association of body composition as well as lifestyle factors as modulators of the age-related changes in RMR and FFW across a broad age range of well-characterized healthy women. Thus the first purpose of this study was to examine associationof severalmetabolic and lifestyle variables as modthe rate of decline of RMR and FFW in a large cohort of ulators of the decline in resting metabolic rate (RMR) and healthy females. Thereafter, we fat-free weight (FFW) in 183 healthy females(18-81 yr). RMR well-characterized sought additional insight into the factors modulating showeda curvilinear decline with age,which was significant in women aged 51-81 yr but not in women aged 18-50 yr. FFW age-related alterations in RMR and FFW by considering showeda curvilinear decline with age, which was significant the influence of physical activity, VO, max, nutritional (P < 0.01) in women 48-81 yr but not in women 18-47 yr. The intake and thyroid hormone status.

Poehlman, Eric T., Michael I. Goran, Andrew W. Gardner, Philip A. Ades, Paul J. Arciero, Shane M. Katzman-Rooks, Stuart M. Montgomery, Michael J. Toth, and Phuong T. Sutherland. Determinants of decline in resting metabolic rate in aging females.Am. J. Physiol. 264 (Endocrinol Metab. 27): E450-E455, 1993.-We consideredthe

declinein RMR wasprimarily associatedwith the lossof FFW (r” = 72%), whereasthe decline in FFW was explained primarily by differences in maximal 0, consumption (\io, max),age, leisuretime physical activity, and dietary protein intake (total r” = 46%). We conclude that RMR and FFW showeda curvilinear decline with agewhich wasacceleratedbeyond the middle-ageyears. Second,the age-relateddecline in RMR wasprimarily associatedwith the lossof FFW. Third, the lossof FFW waspartially related to a decrementin i70, maxand nutritional factors. Therapeutic interventions designedto increaseire, max by elevating physical activity may preservefat-free weight and thus offset the decline of RMR in aging women. thyroid hormones;maximal oxygen consumption DECLINE in resting metabolic rate (RMR) and fat-free weight (FFW) with advancing age is a consistent finding in the scientific literature (2,543, 12, 14, 17, 18,20-22,25-27). Several investigations have attributed the age-related decline in RMR solely to the loss of FFW that loss (25, 26), whereas others have reported of FFW does not fully account for the lower RMR in elderly males (8, 14, 17, 18, 27). Recently, we have suggested that the decline in RMR in males is accelerated beyond the middle-age years and is related both to the loss of FFW as well as a decline in maximal oxygen consumption (V02 max) (14). Although elderly women outnumber elderly men in the population (lo), there is a paucity of data regarding the metabolic determinants of age-related changes in RMR and FFW in females. An earlier study (20) reported a linear decline in RMR in females when data were normalized for body weight or body surface area. Methodological limitations, however, did not permit the assessment of body composition and its relationship with RMR, and sample sizes were limited, especially in the older age ranges. More recent investigations (8, 27) have examined females at the extremes of the age spectrum and have shown that FFW cannot fully account for the lower RMR in older individuals. These studies did not consider the relationship between RMR and body THE

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0193-1849/93

METHODS

Subjects. One hundred and eighty-three healthy females (18-81 yr) participated in this study. Their physical characteristics are presentedin Table 1. All subjectswere characterized by the following: no clinical symptomsor signsof heart disease, resting blood pressureI2 mo in women older than 45 yr. A history of oophorectomy was an exclusionfactor for participation in the study. The averageage of menopausewas 50 t 2 yr in our population. The nature, purpose,and possiblerisks of the study werecarefully explained to each subject before she gave consent to participate. The experimental protocol wasapproved by the Committee on Human Researchfor the Medical Sciencesof the University of Vermont. Timing of measurements.Volunteers were admitted to the Clinical ResearchCenter the afternoon before their metabolic testing at 1600h. Subjectswere fed dinner and were thereafter given practice with the ventilated hood to alleviate any concern or apprehensionover testing conditions. At this point, the Minnesota Leisure Time Physical Activity questionnaire(24) was administered.After an overnight fast in which volunteers slept in the Clinical ResearchCenter, the following tests were performed the next morning: RMR followedby a lo-ml blood draw, underwater weighing, and a test for maximal aerobic power . WO2 max).The specific tests are describedbelow. RMR. RMR was establishedduring the follicular phaseof the menstrual cycle for each subjectby indirect calorimetry for 45 min using a ventilated hood, as previously described(14). The days of the menstrual cycle were numberedbackwardfrom the onset of menstruation (i.e., day 1 was the day before menstruation). Thus, in a typical 28-day cycle, days23 to 15 would

$2.00 Copyright 0 1993 the American Physiological Society

METABOLIC

RATE

AND

FAT-FREE

Table 1. Physical characteristics and energy intake of 183 healthy females Mean

Variable Age,

yr

Ht, m W kg Fat wt, kg Fat-free wt, kg VO 2 IllilX9 l/min VO ml. kg- I . min ’ Leisure time physical activity, Waist-to-hip ratio Daily energy intake, kcal/day Carbohydrate intake, g/day Protein intake, g/day Fat intake, g/day 2

IIlilX9

VO 2 IIlilX9 maximal

kcal/day

+ SD

44t17 1.64t0.07 62t9 f6t7 46t5 2.2kO.6 36.8tll.l 362&230 0.77kO.06 1,843+455 260t75 76t21 48tlO

Range

18-81 1.46-1.82 45-107 6-50 35.1-61.4 1 .o-4.0 15.8-64.4 77-1,278 0.57-0.95 1 ,OOO-3,376 118-395 12-151 30-65

O2 consumption.

be the follicular phase and days 14 to 11 the luteal phase, with ovulation occurring at about day 14. RMR was determined in the same room after an overnight stay (inpatient) in the Clinical Research Center, since these conditions yield lower values than when subjects are tested on an outpatient basis (1). If subjects regularly participated in exercise, metabolic tests were conducted 48 h after their last exercise session to eliminate the residual effect of exercise on metabolic rate (16). Energy expenditure (kcal/day) was calculated from the equation of Weir (28). The reproducibility of RMR in our laboratory has a coefficient of variation of 4.3%. vo 2 rrl~I.Y*VO 2 mt1xwas assessed by a progressive and continuous test to exhaustion on a treadmill as previously described (15). The reproducibility of VO, max in our laboratory has a coefficient of variation of 3.3%. Leisure time physical activity. The estimated energy expenditure in leisure time physical activity (LTA) over the preceding year was assessed in a structured interview using the Minnesota Leisure Time Physical Activity Questionnaire (24). We have previously shown that the Minnesota LTA is correlated (r = 0.83) with the energy expenditure of physical activity derived by the doubly labeled water method in 13 older persons (9). Body composition. Body fat was estimated from body density by underwater weighing using the Keys and Brozek equation (11) with simultaneous measurement of residual lung volume by helium dilution. FFW was estimated as total body weight minus fat weight. For purposes of the present study, FFW was defined as total body weight minus the total fat content of the body (in contrast to the term of lean body mass, which contains some essential lipids). The reproducibility of the measurement of body fat in our laboratory has a coefficient of variation of 4.2%. To estimate upper and lower body fat distribution, a measuring tape was used to determine the waist-to-hip circumference ratio while subjects stood erect. Waist measurements were taken at the minimal circumference of the abdomen, and the hip circumference was measured at the maximal gluteal protuberance of the buttocks. All measurements were performed by the same investigator. Estimated energy intake. Daily energy and macronutrient intake was estimated from a 3-day food diary (2 weekdays, 1 weekend day), as previously described (19). Special attention was given to the importance of subjects maintaining their usual food habits and describing the quantity of food ingested with the aid of a dietary scale, measuring cups and spoons. We attempted to bring individuals in for testing around the midphase of their follicular cycle, so that they could record food intake and be tested during this time period. Thyroid hormone dctcrminutions. Plasma total thyroxine . (T,), free T,, and total triiodothyronine (T:,) concentrations

WEIGHT

IN AGING

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FEMALES

were measured using clinical assay kits (Baxter, Cambridge, MA) and plasma free Ts using an analogue assay (Diagnostic Products, Los Angeles, CA). Statistics. Means, SD, and ranges for each study variable were calculated. Pearson correlations were calculated to estimate the relationship between pairs of variables. Preliminary examination and analyses of data led to the conclusion that the

rate of decreasein several dependent variables with age (i.e., RMR, FFW, total Ts, and free T,) was nonlinear; i.e., a straight line would not adequately represent the relationship between these variables and age. Quadratic regression analysis was applied to examine the curvilinear fit of RMR, FFW, total T,, and free T:, with age. Thereafter, to estimate the point at which the slopeof the dependentvariable may changewith age,segmental

regressionanalysiswas applied to identify the agebreak point(s). Segmental

regression

analysis uses the least-squares

method

to estimate the slopesof the two segmentsas well as the optimum age cut-off point. This model applies when the dependent

variable hasa linear trend over a certain range of the independent variable (age) followed by a linear trend of a different slope over a succeedingagerange. Stepwisemultiple regressionanalysis was applied to determine the best set of predictors for RMR, FFW, total Ts, and free T3. Menopausal status was coded by dummy variables on three levels (1, premenopausal; 2, perimenopausal; 3, postmenopausal) and entered into multiple re-

gressionanalysis.All data are expressedas means& SD. RESULTS

The physical characteristics of the volunteers are displayed in Table 1. These healthy female individuals rep-

resent a broad range of age, VO, max, physical activity level, body composition, and estimated energy intake. The significant (P < 0.01) curvilinear declines in RMR, FFW, and thyroid hormones with age in our sample are depicted in Figs. 1, 2, and 3, respectively. Table 2 summarizes the regression equations and correlations for segmental analysis for RMR, FFW, total T3, and free Ts. There was no significant decline in RMR in females 18-50 yr (r = -0.10; NS), whereas in older females (51-81 yr) a significant decline was noted (r = -0.38; P < 0.01). No significant change in FFW with age in younger females 18-47 yr was found (r = -0.10). Thereafter, a significant decline in FFW was noted in women 48-81 yr (r = -0.39; P < 0.01). No significant change in total T3 and free T3 with age was noted in women 18-42 yr (r = 0.15) and 18-47 yr (r = O.ll), respectively. Thereafter, a significant decline was noted in total T, (r = -0.69; P < 0.01) in females 43-81 yr and in free T3 in women 48-81 yr (r = -0.59; P < 0.01). 1800

-

1600

< Y0

1400

Y U

aL z OL

1200

1000

10

20

30

40 Age

Fig. 1. C urvilinear decli ne in resting with age in 183 healthy females.

50

60

(yrs) metabolic

70

80

rate (RMR,

90

kcal/day)

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METABOLIC

RATE AND FAT-FREE

R=0.40

0

I

i 30 - FFW=47.07+0.0672(Age)-0.002(Age)2 LL I 10

20

30

40

I

=iyroy

70

90

80

Age

Fig. 2. Curvilinear healthy females.

decline in fat-free weight (FFW) with age in 183 180

(A

. l

n=183

l

9

160 c D

140

N

120 0,

2

100

M

80

l-

60 40 10

20

30

40

50

60

70

80

9

3.0

B

I

1 .o 10

n=183

free

T,= 20

1.987+0.01

7(oge)-0.00025(oge)2

30

50

40 Age

60

70

9

80

90

(VI

Fig. 3. Curvilinear decline in total triiodothyronine (B) with age in 183 females.

(T3; A) and free T3

Table 2. Segmental analysis of association of age with resting metabolic rate, fat-free weight, total T,, and free T3 Dependent

Variable

Age, yr

Regression

Equation

Correlation

(r)

(age) -0.10 (age) -0.3f3* -0.10 ~48 (age) FFW, kg -0.39* >48 56.66-0.204 (age) 0.15 c43 116.59+0.38 (age) Total Ta, ng/dl -0.69* 243 200.29- 1.57 (age) 0.11